Computational study of the interplay between intermolecular interactions and CO2 orientations in type I hydrates

Carbon dioxide (CO2) molecules show a rich orientation landscape when they are enclathrated in type I hydrates. Previous studies have described experimentally their preferential orientations, and some theoretical works have explained, but only partially, these experimental results. In the present paper, we use classical molecular dynamics and electronic density functional theory to advance in the theoretical description of CO2 orientations within type I hydrates. Our results are fully compatible with those previously reported, both theoretical and experimental, the geometric shape of the cavities in hydrate being, and therefore, the steric constraints, responsible for some (but not all) preferential angles. In addition, our calculations also show that guest–guest interactions in neighbouring cages are a key factor to explain the remaining experimental angles. Besides the implication concerning equation of state hydrate modeling approximations, the conclusion is that these guest–guest interactions should not be neglected, contrary to the usual practice

DFT calculation of the potential energy landscape topology and Raman spectra of type I CH4 and CO2 hydrates

CO2 and CH4 clathrate hydrates of type I were studied by means of DFT and QTAIM, in order to better understand their properties at the molecular level. Sub-cells of type I hydrates were modeled as independent rigid cages, both empty and containing guest molecules. Interaction potentials of guest molecules inside each cage, and moving from a cell to the adjacent one, were calculated using the DFT approximation B3LYP/6-311+g(d,p), considering the cases with and without long range Coulombic corrections. The selected theory level was validated by comparison of the simulated Raman spectra with the experimental ones, for the case of type I lattice at full occupation of CO2 and CH4, respectively. For this comparison, Fermi resonances of CO2 were taken into account by transforming experimental bands to the corresponding theoretical non-mixed states. On the one hand, our results confirm the validity of the theory level selected for the model. We have shown the high anisotropy of the guest–cell interaction potential of the molecules analyzed, which has implications in the formulation and use of equations of state, and in the study of transport properties as well. On the other hand, our results suggest that the concentration of guest species inside type I hydrates could be computed from the comparison of experimental and predicted Raman spectra, although there are non-trivial experimental limitations to get over for that purpose

Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine

Rituximab, plasma exchange and immunoglobulins: an ineffective treatment for chronic active antibody-mediated rejection

BACKGROUND: Chronic active antibody-mediated rejection (c-aABMR) is an important cause of allograft failure and graft loss in long-term kidney transplants. METHODS: To determine the efficacy and safety of combined therapy with rituximab, plasma exchange (PE) and intravenous immunoglobulins (IVIG), a cohort of patients with transplant glomerulopathy (TG) that met criteria of active cABMR, according to BANFF'17 classification, was identified. RESULTS: We identified 62 patients with active c-aABMR and TG (cg ≥ 1). Twenty-three patients were treated with the combination therapy and, 39 patients did not receive treatment and were considered the control group. There were no significant differences in the graft survival between the two groups. The number of graft losses at 12 and 24 months and the decline of eGFR were not different and independent of the treatment. A decrease of eGFR≥13 ml/min between 6 months before and c-aABMR diagnosis, was an independent risk factor for graft loss at 24 months (OR = 5; P = 0.01). Infections that required hospitalization during the first year after c-aABMR diagnosis were significantly more frequent in treated patients (OR = 4.22; P = 0.013), with a ratio infection/patient-year of 0.65 and 0.20 respectively. CONCLUSIONS: Treatment with rituximab, PE, and IVIG in kidney transplants with c-aABMR did not improve graft survival and was associated with a significant increase in severe infectious complications

Is it possible to diagnose the therapeutic adherence of patients with COPD in clinical practice? A cohort study

<p>Abstract</p> <p>Background</p> <p>Therapeutic adherence of patients with chronic obstructive pulmonary disease (COPD) is poor. It is therefore necessary to determine the magnitude of non-adherence to develop strategies to correct this behaviour. The purpose of this study was to analyse the diagnostic validity of indirect adherence methods.</p> <p>Methods</p> <p>Sample: 195 COPD patients undergoing scheduled inhaled treatment attending 5 Primary Care Centres of Malaga, Spain. Variables: Sociodemographic profile, illness data, spirometry, quality of life (St. George Respiratory Questionnaire: SGRQ), and inhaled medication counting (count of dose/pill or electronic monitoring) were collected. The patient's knowledge of COPD (Batalla test:BT),their attitude towards treatment (Morisky-Green test: MGT) and their self-reported therapeutic adherence (Haynes-Sackett test: HST) were used as methods of evaluating adherence. The follow-up consisted four visits over one year (the recruitment visit: V0; and after 1 month:V1; 6 months:V2; and 1 year:V3).</p> <p>Results</p> <p>The mean age was 69.59 (95% CI, 68.29-70.89) years old and 93.8% were male. Other findings included: 85.4% had a low educational level, 23.6% were smokers, 71.5% mild-moderate COPD stage with a FEV1 = 56.86 (SD = 18.85); exacerbations per year = 1.41(95% CI, 1-1.8). The total SGRQ score was 44.96 (95% CI, 42.46-47.46), showing a mild self-perceived impairment in health. The prevalence of adherence (dose/pill count) was 68.1% (95% CI, 60.9-75.3) at V1, 80% (95% CI, 73-87) at V2 and 84% (95% CI, 77.9) at V3. The MGT showed a specificity of 67.34% at V1, 76.19% at V2 and 69.62% at V3. The sensitivity was 53.33% at V1, 66.66% at V2 and 33.33% at V3.The BT showed a specificity of 55.1% at V1, 70.23% at V2 and 67.09% at V3. The sensitivity was 68.88% at V1, 71.43% at V2 and 46.66% at V3. Considering both tests together, the specificity was 86.73% at V1, 94.04% at V2 and 92.49% at V3 and the sensitivity was 37.77% at V1, 47.62% at V2 and 13.3% at V3.</p> <p>Conclusions</p> <p>The prevalence of treatment adherence changes over time. Indirect methods (dose/pill count and self-reported) can be useful to detect non-adherence in COPD patients. The combination of MGT and BT is the best approach to test self-reported adherence.</p

Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease

© 2021, The Author(s). Aging and Alzheimer’s disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD

Hard Two-Photon Contribution to Elastic Lepton-Proton Scattering: Determined by the OLYMPUS Experiment

The OLYMPUS collaboration reports on a precision measurement of the positron-proton to electron-proton elastic cross section ratio, $R_{2\gamma}$, a direct measure of the contribution of hard two-photon exchange to the elastic cross section. In the OLYMPUS measurement, 2.01~GeV electron and positron beams were directed through a hydrogen gas target internal to the DORIS storage ring at DESY. A toroidal magnetic spectrometer instrumented with drift chambers and time-of-flight scintillators detected elastically scattered leptons in coincidence with recoiling protons over a scattering angle range of $\approx 20\degree$ to $80\degree$. The relative luminosity between the two beam species was monitored using tracking telescopes of interleaved GEM and MWPC detectors at $12\degree$, as well as symmetric M{\o}ller/Bhabha calorimeters at $1.29\degree$. A total integrated luminosity of 4.5~fb$^{-1}$ was collected. In the extraction of $R_{2\gamma}$, radiative effects were taken into account using a Monte Carlo generator to simulate the convolutions of internal bremsstrahlung with experiment-specific conditions such as detector acceptance and reconstruction efficiency. The resulting values of $R_{2\gamma}$, presented here for a wide range of virtual photon polarization $0.456<\epsilon<0.978$, are smaller than some hadronic two-photon exchange calculations predict, but are in reasonable agreement with a subtracted dispersion model and a phenomenological fit to the form factor data.Comment: 5 pages, 3 figures, 2 table

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration—which is shorter than current recommendations